Distinguishing paintings from photographs Florin Cutzu, Riad Hammoud, Alex Leykin * Department of Computer Science, Indiana University, Bloomington, IN 47405, USA Received 24 October 2002; accepted 6 December 2004 Abstract We addressed the problem of automatically differentiating photographs of real scenes from photographs of paintings. We found that photographs differ from paintings in their color, edge, and texture properties. Based on these features, we trained and tested a classifier on a database of 6000 paintings and 6000 photographs. Using single features results in 70–80% correct discrimination performance, whereas a classifier using multiple features exceeds 90% correct discrimination. Ó 2005 Published by Elsevier Inc. Keywords: Color edges; Image classification; Image features; Image databases; Neural networks; Painti- ngs; Photorealism; Photographs 1. Introduction 1.1. Problem statement The goal of the present work was the determination of the image features distin- guishing photographs of real-world, three-dimensional, scenes from (photographs of) paintings and the development of a classifier system for their automatic differentiation. 1077-3142/$ - see front matter Ó 2005 Published by Elsevier Inc. doi:10.1016/j.cviu.2004.12.002 * Corresponding author. Fax: +1 812 855 4829. E-mail addresses: florin@cs.indiana.edu (F. Cutzu), rhammoud@cs.indiana.edu (R. Hammoud), oleykin@cs.indiana.edu (A. Leykin). www.elsevier.com/locate/cviu Computer Vision and Image Understanding xxx (2005) xxx–xxx ARTICLE IN PRESS